<h1 id="frankenstein-model-suite:-experimental-grounds-j3lqj9z9v"><strong><span style="color:#82c91e">Frankenstein</span> - Model Suite: Experimental Grounds</strong></h1><ul><li><p><strong><span style="color:#fa5252">Warning</span>: <span style="color:#868e96">Highly Experimental Models Ahead! Proceed with Curiosity (and Caution)!</span></strong><br /></p></li></ul><p>Welcome to the laboratory! The Frankenstein Model Suite is where I unleash my more... <em>unconventional</em> creations. Unlike my refined models such as Everlasting, the models hosted here are born from experimental merges, unusual training techniques, bespoke modification scripts, and sometimes, sheer chaotic curiosity.<br /></p><p>Think of this as a collection of works-in-progress, oddities, and boundary-pushing attempts. They are stitched together using various methods, potentially including techniques developed with my custom-crafted merger tool and other experimental approaches</p><p></p><h1 id="methods-swyyt7bg3"><br />Methods</h1><h3 id="block-swap-(bs-custom-merger-implementation):-instead-of-blending-weights-this-method-swaps-entire-architectural-blocks-(like-input-middle-or-output-sections-of-the-u-net)-between-models-based-on-certain-rules.-it-aims-to-combine-functional-strengths-but-risks-incompatibility-between-the-stitched-sections.-(highly-experimental-but-functional)-dqdshklhw"><em> </em><span style="color:#fab005">Block Swap (BS - Custom Merger Implementation):</span> Instead of blending weights, this method swaps entire architectural blocks (like input, middle, or output sections of the U-Net) between models based on certain rules. It aims to combine functional strengths but risks incompatibility between the stitched sections. <em>(HIGHLY EXPERIMENTAL BUT FUNCTIONAL)</em></h3><h3 id="latent-resonance-tuning-(lrt):-attempts-to-identify-key-latent-features-in-one-model-and-subtly-amplify-corresponding-weights-in-another-trying-to-make-the-second-model-&quot;resonate&quot;-with-the-first-model's-specific-strengths-at-a-feature-level.-(experimental)-hxf26w1r6"><em> </em><span style="color:#82c91e">Latent Resonance Tuning (LRT):</span> Attempts to identify key latent features in one model and subtly amplify corresponding weights in another, trying to make the second model "resonate" with the first model's specific strengths at a feature level. <em>(EXPERIMENTAL)</em></h3><h3 id="gradient-harmonic-injection-(ghi):-involves-injecting-scaled-gradients-from-a-parent-model-during-a-post-merge-fine-tuning-phase-attempting-to-subtly-steer-the-merged-model-towards-a-parent's-style-without-full-retraining.-(experimental)-hneb20nox"><em> </em><span style="color:#12b886">Gradient Harmonic Injection (GHI):</span> Involves injecting scaled gradients from a parent model during a post-merge fine-tuning phase, attempting to subtly steer the merged model towards a parent's style without full retraining. <em>(EXPERIMENTAL)</em></h3><h3 id="cross-attention-splicing-(cas):-mixes-components-of-the-cross-attention-mechanism-(e.g.-querykey-matrices-from-one-model-valueprojection-from-another)-to-blend-how-models-interpret-prompts-with-how-they-apply-that-interpretation.-(experimental)-cmfg4foda"><em> </em><span style="color:#40c057">Cross-Attention Splicing (CAS):</span> Mixes components of the cross-attention mechanism (e.g., query/key matrices from one model, value/projection from another) to blend how models interpret prompts with how they apply that interpretation. <em>(EXPERIMENTAL)</em></h3><h3 id="denoising-path-scaffolding-(dps):-uses-parts-of-a-parent-model's-u-net-to-temporarily-guide-or-replace-calculations-at-specific-steps-within-the-merged-model's-denoising-process.-(experimental)-td3gktpm7"><em> </em><span style="color:#15aabf">Denoising Path Scaffolding (DPS):</span> Uses parts of a parent model's U-Net to temporarily guide or replace calculations at specific steps within the merged model's denoising process. <em>(EXPERIMENTAL)</em></h3><p></p><p></p><h1 id="what-to-expect:-aa9c62ryr"><strong>What to Expect:</strong></h1><h3 id="unpredictability:-results-can-vary-wildly.-what-works-for-one-prompt-might-break-on-another.-expect-the-unexpected!-9b8klk2ay"><em> </em><span style="color:#e64980">Unpredictability:</span> Results can vary wildly. What works for one prompt might break on another. Expect the unexpected!</h3><h3 id="potential-instability:-some-models-might-produce-artifacts-glitches-or-struggle-with-coherence-more-than-polished-releases.-hands-feet-and-eyes-might-be-even-more-challenging-than-usual.-ppiizz4th"><em> </em><span style="color:#fd7e14">Potential Instability:</span> Some models might produce artifacts, glitches, or struggle with coherence more than polished releases. Hands, feet, and eyes might be even more challenging than usual.</h3><h3 id="niche-capabilities:-a-model-here-might-do-one-very-specific-thing-interestingly-but-be-terrible-at-everything-else.-qc8c4ajj6"><em> </em><span style="color:#fab005">Niche Capabilities:</span> A model here might do one <em>very specific</em> thing interestingly, but be terrible at everything else.</h3><h3 id="occasional-gems:-sometimes-the-chaos-yields-surprisingly-unique-aesthetics-or-combinations-you-won't-find-elsewhere!-4abne7kz9"><em> </em><span style="color:#4c6ef5">Occasional Gems:</span> Sometimes, the chaos yields surprisingly unique aesthetics or combinations you won't find elsewhere!</h3><p></p><p></p><h1 id="why-this-suite-exists:-qerre5t5d"><strong>Why This Suite Exists:</strong></h1><p>This is a space for open experimentation and sharing explorations that aren't quite ready for a "stable" release. It's a chance to play with rougher ideas and see what strange beauty (or monstrosity) might emerge. Your feedback and discoveries – good, bad, or just plain weird – are part of the experiment!</p><p></p><p></p><h2 id="recommended-settings:-iu6bj7ndc"><strong>Recommended Settings:</strong></h2><h3 id="highly-model-dependent!-there-are-no-universally-recommended-settings-here.-check-individual-model-notes-if-available.-cbik6jnd0"><em> </em><span style="color:#e64980">Highly Model-Dependent!</span> There are NO universally recommended settings here. Check individual model notes if available.</h3><h3 id="starting-point:-you-can-start-with-common-settings-(e.g.-sampler:-euler-a-steps:-20-30-cfg-scale:-5-7-clip-skip:-1-2)-but-be-prepared-to-experiment-heavily.-vemzhvrcx"><em> </em><span style="color:#15aabf">Starting Point:</span> You <em>can</em> start with common settings (e.g., <code>Sampler: Euler a</code>, <code>Steps: 20-30</code>, <code>CFG Scale: 5-7</code>, <code>Clip Skip: 1-2</code>), but <strong>be prepared to experiment heavily.</strong></h3><h3 id="prompting:-some-models-might-require-very-specific-trigger-words-or-prompt-structures.-others-might-ignore-negative-prompts-entirely-or-react-strangely-to-them.-pay-attention-to-any-included-examples.-luk5yakd6"><em> </em><span style="color:#82c91e">Prompting:</span> Some models might require very specific trigger words or prompt structures. Others might ignore negative prompts entirely or react strangely to them. Pay attention to any included examples.</h3><h3 id="denoising:-for-img2img-or-refining-outputs-denoising-strength-might-need-careful-tuning-(try-ranges-like-0.5-0.75).-3ro7zo5xa"><span style="color:#7950f2"> Denoising:</span> For img2img or refining outputs, denoising strength might need careful tuning (try ranges like 0.5-0.75).</h3><p></p><p>Usage Guidelines:</p><p> *Non-commercial Use:** Primarily intended for personal experimentation and non-commercial creative exploration. Please generate responsibly.</p><p> *Sharing:** Feel free to share your generations. If sharing the models themselves, please link back here and keep the experimental nature crystal clear.</p><p> *Attribution:** When sharing results, mentioning the specific model name and technique (if known) from the Frankenstein Suite helps track these experiments.</p><p> *Feedback Welcome:** If you find interesting settings, prompts, or use cases (or run into spectacular failures), sharing your findings can be valuable!</p><p></p><pre><code>Dive in, experiment (safely!), and let's see what these stitched-together creations can do!</code></pre><p></p>

Frankenstein - Model Suite

<p>This is a block swap between ill v2.0 and everlasting with a experimental grey shift stripping, this removes the grey fuzz and dull colors but results in over contras (Does take loras and loras fix some contras issues) This model results in smooth colors and smooth lines with good line separation between character and background <br /><br />This model has first step instability so the more steps the better + use hiresFix to bring back detail</p>

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